Control Of Reaction Temperature Research Articles

From simulation to reality: CFD-ML-driven structural optimization and experimental analysis of thermal plasma reactors

Thermal plasma reactors offer an environment of high temperature, enthalpy, and reactivity, making them highly efficient for solid waste treatment and promising for clean energy production from municipal and industrial waste. Optimal geometrical parameters of the reactor can enhance waste treatment and reactor performance. This study presents a comprehensive analysis of 11 key geometrical parameters of a thermal plasma reactor. Utilizing CFD Fluent software, numerical simulations were conducted to generate a dataset. Subsequently, a predictive model focusing on the average temperature in the core melt zone was trained using six Machine Learning (ML) algorithms. The Particle Swarm Optimisation (PSO) algorithm optimized the hyperparameters of the Gradient Booster Regression (GBR) model, which was combined with a Genetic Algorithm (GA) to identify the reactor's optimal geometrical parameters. A DC arc plasma torch-solid waste thermal plasma reactor treatment system was established on this basis. The study also explored the effects of gasification coefficient, reaction temperature, and thermal plasma jet mode on system performance. Findings indicate that the PSO-GBR model achieved the highest prediction accuracy, with the temperature in the core reaction zone reaching 3621 K. The deviation between numerical simulations and machine learning predictions was a mere 1.3%. Enhancing syngas yield and energy efficiency is achievable by controlling reaction temperature and increasing the gasification coefficient. A laminar plasma jet mode, at equal power, provides a more effective reaction environment. The accuracy and reliability of the machine learning-driven regression model and optimization results are significant in guiding the optimal design of plasma reactors and advancing waste-to-energy conversion processes.

Temperature control strategy for safer and heat-efficient operations in a catalytic flow reactor

A new temperature control strategy for a packed-bed tubular reactor was proposed. Case studies of a highly exothermic 1st-order reaction and an actual 2nd-order reaction were conducted using the computational fluid dynamics software COMSOL Multiphysics® 4.4. Through the simulation, the important factors for reactor temperature control were confirmed, which were the parameters related to heat transfer. Based on the ratio of the heat generation rate to the heat transfer rate, a new dimensionless number was proposed for controlling the temperature increase within an acceptable range in a reactor. Through case studies, the validity of the proposed dimensionless number was confirmed, and an important value of a proportionality constant was derived from the results. Using the proposed dimensionless number, a reactor size can be maximized within an acceptable temperature increase. The results obtained in this study are expected to provide important guidelines for temperature control and maximization of production using flow reactors.

Sliding mode control for gasifier reactor temperature control

This paper presents a sliding mode control (SMC) design for gasifier reactor temperature control. Temperature control is a critical aspect of biomass gasification for quality syngas production. However, accurate modeling and effective control method are the major challenges of gasifier reactor temperature control. The gasification system processes are not yet well understood to model from the first principle due to the complex and nonlinear nature of the process. Also, conventional control methods such as proportional, integral, and derivative control have not been effective in controlling gasification systems. Hence, this work has used experimental data from a 500 kVA updraft gasifier reactor to develop a data-driven mathematical model. The system identification result predicts 86.36% goodness of fit on the model data and 88.26% on the validation data. Discrete time sliding mode control has been designed from the model and implemented in Simulink to investigate the performance of the control method on the gasifier. The result of the system time response shows that the controller effectively drives the temperature monotonically from 25°C to 700 °C in finite time (11.37 minutes). It also establishes a quasi-sliding motion with an ultimate band of ±1℃ for the remainder of the simulation time. Hence, the control technique guarantees optimal temperature control for any feedstock type which will result in higher conversion efficiency, more syngas yield, and improve syngas quality and durability of the gasifier reactor among others.

Plantwide Simulation and Operation of a Methanol to Propylene (MTP) Process

BackgroundMethanol to propylene (MTP) process is considered as one of the most important methods for propylene production. The MTP process consists of four sections: conversion of reactants to products, cooling, compression and products separation. In this process, is utilized from multi-stage fixed bed reactors. Due to high exothermicity of the MTP reactors, and existence of recycle loops, a plant-wide control structure is required to be designed for stable, safe and maximum production of propylene. MethodModeling and simulation of the heterogeneous fixed bed MTP reactors with interphase and intra-particle mass and heat transfer were carried out in Aspen Custom Modeler. Steady-state simulations of the MTP process were carried out in Aspen Plus. A simple control strategy was proposed to achieve maximum propylene production with temperature control of the MTP multi-stage reactors by splitting the cold oxygenate feed and the recycled hydrocarbons among the reactor beds. The performance of the proposed control strategy was tested against several disturbances including change in flowrate and composition of feed, using dynamic simulations by Aspen Plus Dynamics. Significant findingDynamic simulation results revealed that simultaneous control of the split range for the 5th and 6th reactor beds and cascade temperature of other reactor beds, could be a suitable temperature control strategy for the reaction section of the MTP process.

Reductant-free synthesis conditions for water-dispersible reduced graphene oxide

Reduced graphene oxide (rGO) is the demanded material for large-scale graphene applications due to the relative ease of preparing sufficient quantities with the desired properties. Herein, optimized preparation conditions for water-dispersible rGO using the one-step chemical exfoliation method are reported. The rGO samples were obtained from graphite under different controlled reaction conditions, i.e., temperature (120, 140, and 160 °C) and time (16, 20, and 24 hrs). The microstructural, chemical, wetting, and electrical properties of samples were characterized using Raman spectroscopy, X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectroscopy, contact angle measurement, current-voltage (I–V) characteristic, and electrochemical impedance spectroscopy (EIS), respectively. The Raman parameter (i.e., the ID/IG values) was used to assess the quality of rGO materials. Accordingly, rGO160@20 showed the smallest ID/IG value (0.57) compared to the rest of the samples, followed by rGO160@16 and rGO120@24 with 0.75 and 0.77 values, respectively. The observed broad and diffused peaks centered at 2θ = 25° from XRD are the finger-print characteristics of rGO samples. FT-IR (mainly due to -OH) and lower contact angle values (≤ 33 °C) analysis confirmed the hydrophilic nature of these samples. The samples' non-linear I-V characteristics were attributed to disordered dielectric barriers. The charge transfer resistances (Rct) at the electrode/electrolyte interface were 21.65 for rGO160@20 and 25.65 for rGO160@16 and rGO120@24. EIS analysis also confirmed the rGO samples have supercapacitor behavior. Experimental parameters' synergistic effects influenced sample microstructure. Optimal processing conditions of rGO samples were also achieved for energy storage and applications that need graphene water dispersion.

NaOH and temperature-induced formation of Bi-based BixOyBrz photocatalyst for phenol degradation

In this work, Bi-based BixOyBrz photocatalyst including BiOBr, Bi2O3/Bi4O5Br2, BiOBr/Bi4O5Br2 and Bi4O5Br2 were successfully prepared by adding NaOH and controlling reaction temperature. BiOBr/Bi4O5Br2 composite displayed excellent photocatalytic activity for phenol degradation compared with other Bi-based BixOyBrz photocatalyst. Toxicity experiments suggested that low environmental toxicity of BiOBr/Bi4O5Br2 composite for the growth state of Sudangrass seeds and Mung bean seeds. A BiOBr/Bi4O5Br2 S-scheme heterojunction was proposed to explain the photocatalytic degradation mechanism.

A route to metalloligands consolidated silver nanoclusters by grafting thiacalix[4]arene onto polyoxovanadates

Metalloligands provide a potent strategy for manipulating the surface metal arrangements of metal nanoclusters, but their synthesis and subsequent installation onto metal nanoclusters remains a significant challenge. Herein, two atomically precise silver nanoclusters {Ag14[(TC4A)6(V9O16)](CyS)3} (Ag14) and {Ag43S[(TC4A)2(V4O9)]3(CyS)9(PhCOO)3Cl3(SO4)4(DMF)3·6DMF} (Ag43) are synthesized by controlling reaction temperature (H4TC4A = p-tert-butylthiacalix[4]arene). Interestingly, the 3D scaffold-like [(TC4A)6(V9O16)]11- metalloligand in Ag14 and 1D arcuate [(TC4A)2(V4O9)]6- metalloligand in Ag43 exhibit a dual role that is the internal polyoxovanadates as anion template and the surface TC4A4- as the passivating agent. Furthermore, the thermal-induced structure transformation between Ag14 and Ag43 is achieved based on the temperature-dependent assembly process. Ag14 shows superior photothermal conversion performance than Ag43 in solid state indicating its potential for remote laser ignition. Here, we show the potential of two thiacalix[4]arene modified polyoxovanadates metalloligands in the assembly of metal nanoclusters and provide a cornerstone for the remote laser ignition applications of silver nanoclusters.

Biomimic Zwitterionic Polyamide/Polyurethane Elastic Blending Fabrics.

This study developed an epoxy-type biomimic zwitterionic copolymer, poly(glycidyl methacrylate) (PGMA)-poly(sulfobetaine acrylamide) (SBAA) (poly(GMA-co-SBAA)), to modify the surface of polyamide elastic fabric using a hydroxylated pretreatment zwitterionic copolymer and dip-coating method. X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy confirmed successful grafting, while scanning electron microscopy revealed changes in the surface pattern. Optimization of coating conditions included controlling reaction temperature, solid concentration, molar ratio, and base catalysis. The modified fabric exhibited good biocompatibility and anti-biofouling performance, as evidenced by contact angle measurements and evaluation of protein adsorption, blood cell, and bacterial attachment. This simple, cost-effective zwitterionic modification technology has high commercial value and is a promising approach for surface modification of biomedical materials.

Effect of Temperature-controlled conditions on the decomposition of particulate matter deposited in the diesel particulate filter channel by treatment with Non-thermal plasma

The regeneration effect of the diesel particulate filter (DPF) under steady-state and dynamically controlled reaction temperature (≤200C) was compared using a home-designed non-thermal plasma (NTP) injection system. The particle sediments and corresponding DPF channel wall were sampled as a whole, in order to analyze the evolution of the micromorphology, lattice structure and oxidation characteristics of particulate matter (PM) at the DPF regeneration interface more accurately. The results showed that after NTP treatment, the degree of aggregation of PM, the transition to a chain structure, and the diameter of primary carbon particles all decreased. The microcrystalline length La distribution converged in a short crystalline (≤1.00 nm) interval, and the proportion of small microcrystalline layer spacing Ds (≤0.45 nm) increased. With the deepening of oxidation, the characteristic temperature parameters of elemental carbon (EC), the light off temperature Ts, burnout temperature Te and maximum temperature Tmax tended to shift to a lower temperature, and lattice defects, number of active sites, and PM oxidation activity increased. Dynamic control of the reaction temperature in the range of 127 ∼ 142 ℃ can promote the oxidative decomposition of PM, which is conducive to improving the regeneration efficiency of the DPF. The process of NTP degradation of PM consists of three stages, namely the outer shell, inner shell and core oxidation, and carbon microcrystals are exhausted in the iterative process of irregular and regular structure, which is essentially a process of continuously removing carbon atoms in the form of COx.

Continuous Reactor Temperature Control with Optimized PID Parameters Based on Improved Sparrow Algorithm

To address the problems of strong coupling and large hysteresis in the temperature control of a continuously stirred tank reactor (CSTR) process, an improved sparrow search algorithm (ISSA) is proposed to optimize the PID parameters. The improvement aims to solve the problems of population diversity reduction and easy-to-fall-into local optimal solutions when the traditional sparrow algorithm is close to the global optimum. This differs from other improved algorithms by adding a new Gauss Cauchy mutation strategy at the end of each iteration without increasing the time complexity of the algorithm. By introducing tent mapping in the sparrow algorithm to initialize the population, the population diversity and global search ability are improved; the golden partition coefficient is introduced in the explorer position update process to expand the search space and balance the relationship between search and exploitation; the Gauss Cauchy mutation strategy is used to enhance the ability of local minimum value search and jumping out of local optimum. Compared with the four existing classical algorithms, ISSA has improved the convergence speed, global search ability and the ability to jump out of local optimum. The proposed algorithm is combined with PID control to design an ISSA-PID temperature controller, which is simulated on a continuous reactor temperature model identified by modeling. The results show that the proposed method improves the transient and steady-state performance of the reactor temperature control with good control accuracy and robustness. Finally, the proposed algorithm is applied to a semi-physical experimental platform to verify its feasibility.

Reactor Temperature Control Based on Improved Fractional Order Self-Anti-Disturbance

In the chemical industry, a reactor is an absolutely necessary container. The fact that its dynamic qualities are nonlinear and unknown, however, is what causes the temperature to deviate from the value that was specified. As a result, the typical PID control cannot fulfill the prerequisites of the production process. A new nonlinear function is presented to replace the function that was previously used, and a temperature controller that is based on better fractional order active disturbance rejection is devised. On the basis of a new fractional order temperature detector (FOTD), a new fractional order equilibrium state observer (FOESO), and nonlinear function, an improved fractional order active disturbance rejection controller has been developed. A model of the reactor was created, and the dynamic properties of temperature control were investigated. By simulation and experimentation, it was demonstrated that the strategy has a number of benefits and is effective. In this approach, the information provided by the model is exploited to its maximum potential, and the temperature of the inlet cooling water is employed as the temperature control disturbance for feedforward compensation. Over the entirety of the process, this guarantees that the desired temperature will be preserved. When compared to FADRC, PID, and ADRC, the rising time is increased by 5 s, and the overshoot is raised by 25%. It has been established that the fraction-order active disturbance rejection controller has a quicker response speed, a higher capacity for anti-interference, and a quicker speed of stabilization.

Preparation of n-Octadecane@MF resin microPCMs and its application in temperature control of esterification reactions

Reaction thermal runaway accidents occur frequently and occupy a high proportion in chemical accidents. Reducing accidents by controlling reaction temperature is of great implication to enhance the safety level of chemical processes. Phase change materials (PCMs) have a good energy storage potential, which can rapidly convert the reaction exotherm in the reaction process into its own phase change latent heat, urgently control the reaction temperature, and enhance the process thermal safety level. In this study, using n-octadecane as the core and melamine-formaldehyde (MF) resin as the shell, microencapsulated phase change materials (microPCMs) was made, which has a smooth spherical shape, good thermal stability, and a phase change enthalpy up to 162.87 J/g. The homogeneous esterification reaction of 2-butanol (2 B) and propionic anhydride (PA) was selected as the target reaction, and then the reaction was scaled up equivalently to investigate the effect of amplification to the reaction system. The results indicated that the temperature control of the esterification reaction system by microPCMs is the synergy between physical inhibition and chemical inhibition. The reaction temperature could be controlled by adding microPCMs, and the temperature control effect improved with the increase of microPCMs addition. In large scale reactors, microPCMs still has certain temperature control ability after being added.

Control of reactor temperature and pressure using cascade control during polyvinyl chloride production

Improvement and modernization of the technological process of polyvinyl chloride production requires the appropriate development of computer modelling systems, which ensure the following: identification and maintenance of optimal modes of technological processes that contribute to continuous operation, as well as the use of intelligent systems of modelling and control of technological devices. The article proposes pressure-dependent control of the temperature in the reactor, which affects the quality indicators of the technological process, using the cascade control method during the production of polyvinyl chloride. In this work an imitation model of the technological process was developed.

Two Stable Cd-MOFs as Dual-Functional Materials with Luminescent Sensing of Antibiotics and Proton Conduction.

Construction and investigation of dual-functional metal-organic frameworks (MOFs) with luminescent sensing and proton conduction provide widespread applications in clean energy and environmental monitoring fields. By selecting a phosphonic acid ligand 4-pyridyl-CH2N(CH2PO3H2)2 (H4L) and coligand 2,2'-biimidazole (H2biim), two cadmium-based MOFs [Cd1.5(HL)(H2biim)0.5] (1) and (H4biim)0.5·[Cd2(L)(H2biim)Cl] (2) with different structures and properties have been hydrothermally synthesized by controlling reaction temperature. Based on the excellent thermal and chemical stabilities, and good luminescent stabilities in water solution, 1 and 2 can serve as luminescent sensors of chloramphenicol (CAP) with different quenching constant (KSV) values and detection limits (LODs) in water, simulated environmental system, and real fish water system. Meanwhile, different sensing effects and possible sensing mechanisms are analyzed in detail. Moreover, 1 and 2 can also serve as good proton-conducting materials. The proton conductivities can reach up to 1.41 × 10-4 S cm-1 for 1 and 1.02 × 10-3 S cm-1 for 2 at 368 K and 95% relative humidity (RH). Among them, 2 shows better luminescent sensing and proton conduction performance than 1, which indicates that different crystal structures have a great impact on the properties of MOFs. Through the discussion of the relationship between structures and properties in detail, the possible reasons for the differences in properties are obtained, which can provide theoretical guidance for the rational design of this kind of dual-functional MOFs in the future.

Synthesis of poly(hydroxyethyl methacrylate)‐b‐poly(propylene glycol)‐b‐poly(hydroxyethyl methacrylate)reactive block copolymer with controlled reactivity for toughening multifunctional epoxy resin

AbstractMultifunctional epoxy resins are inherently brittle due to the extremely high cross‐linking density, thus the enhancement in the toughness is rather important for the industrial application. In this work, a reactive poly(hydroxyethyl methacrylate)‐b‐poly(propylene glycol)‐b‐poly(hydroxyethyl methacrylate) (PHEMA‐PPG‐PHEMA) is synthesized by using an atom transfer radical polymerization to toughen trifunctional diglycidyl 4,5‐epoxy cyclohexane‐1,2‐dicarboxylate (TDE‐85). A controllable system is constructed, in which the reaction temperature of TDE‐85 with the hydroxyl of PHEMA‐PPG‐PHEMA is lower than with the curing agent. As a result, both heterogeneous and homogeneous structures can be formed in composites through controlling reaction temperature. It is found that the toughness of composites with the heterogeneous structure is effectively improved without sacrificing the tensile strength, tensile modulus, and glass transition temperature. Specifically, the mode‐1 critical stress intensity factor and critical strain energy release rate of TDE‐85/10 wt% PHEMA‐PPG‐PHEMA are increased to 0.77 MPam1/2 and 146 J/m2, respectively, which are effectively enhanced by 32.8% and 70.3%. This can be ascribed to combined toughening effects from the cavitation of the PHEMA‐PPG‐PHEMA phase, the matrix shear yielding, and the enhanced interface bonding strength due to the reaction between TDE‐85 and PHEMA‐PPG‐PHEMA. Thus, this study paves a novel strategy to improve the toughness of epoxy resin by controlling the curing reaction.

Data-driven adaptive predictive control of hydrocracking process using a covariance matrix adaption evolution strategy

In this paper, a new data-driven adaptive predictive control architecture to the reactor temperature control problem in hydrocracking process is proposed with completely unknown system dynamics. Specifically, the nonlinear relationship between the reactor temperature and conversion is established using echo state networks (ESNs) with an intrinsic plasticity rule, and a covariance matrix adaption evolution strategy (CMA-ES) is used to optimize the reactor temperature iteratively using the input and state information. Besides, the prescribed performance function is introduced to guarantee the transient and steady performance of the system. In addition, the input constraints and external disturbance are simultaneously considered. Numerical simulation results and industrial application prove the efficacy of the proposed method.

A novel cascaded fractional fuzzy approach for control of fermentation process

In this work, a cascaded control strategy based on fractional-order fuzzy PD/PI (FOFPD/PI) is proposed for temperature control of the bioreactor. The FOFPI is used to control the ethanol concentration in the inner loop, while the FOFPD is used for temperature control of the bioreactor in the outer loop. The integer order fuzzy PD/PI (IOFPD/PI), 2DOF FOPID, 2DOF PID, and PID are also designed for comparison purposes. The design parameter of FOFPD/PI and IOFPD/PI are estimated using non-dominated sorting genetic algorithm II (NSGA-II). Results revealed that the proposed cascaded control scheme reduced the IAE by 33.5 %, 40.5%, 47%, and 64% compared to IOFPD/PI, 2DOF FOPID, 2DOF PID, and PID, respectively. Hence, it can be concluded that the proposed FOFPD/PI controller provides precise control of reactor temperature in different operating conditions compared to other controllers.

Analysis of CSTR Temperature Control with PID, MPC & Hybrid MPC-PID Controller

This paper presents an analysis of the continuous stirred tank reactor (CSTR) temperature control with the Proportional-Integral-Derivative (PID) Controller, Model Predictive Controller (MPC) and Hybrid-Model Predictive Controller-Proportional Integral Derivative Controller (MPC-PID). It is the main goal of this project to find a suitable improvement strategy for the system’s stability and accuracy to be more stable. By creating a model, the control system is implemented for all the above mentioned control methods and so comparative analysis is carried out to find the best control method for CSTR. Simulation data inspector is used to compare the performance of different types of control systems: PID, MPC and MPC-PID. It has been observed that the hybrid MPC-PID has a more effective control action than a PID controller; with some tuning, the MPC controller can maintain the temperature within a reference or set point range. The control and simulation toolbox is used to construct the model predictive control method in LabVIEW platform. The performance of controllers is measured in terms of settling time, rise time and percentage of overshoot. Finally, a comparative overview of PID, MPC and Hybrid MPC-PID controllers on system performance is presented and discussed.

Modelling, control and supervisory optimization of generalized predictive control in catalytic cracking reactor

Abstract As gasoline demand increases, the efficiency of operation of Fluidized Catalytic Cracking Unit (FCCU) becomes paramount importance. In this paper, a dynamic model for FCCU is simulated and integrated with yield model in order to estimate the yield of products namely gasoline, light gases and coke. Conventional PI controllers are designed for the control of reactor and regenerator temperature. Since, the complete reaction occurs in a very short duration, the controllers are tuned so as to achieve shorter settling time and minimum overshot. Further in order to increase the yield, optimization of FCCU using Generalized Predictive Controller (GPC) at supervisory level is attempted. Through optimization of objective function, the GPC will provide optimized set point for the PI controller in order to maintain maximum gasoline yield.

Dynamics of hybrid nanofluid through a semi spherical porous fin with internal heat generation

Semi-spherical fins are widely considered to be one of the best thermal exchangers available. It is widely employed, including aero planes, chemicals and electronic kits and porous medium is an extensive application that includes drying efficiency enhancement, filtering insulations, hydraulic oils, reactor temperature control and solar collectors. With these applications in perspective, the current study uses Darcy’s model to examine the performance of hybrid nanofluids flowing over a semi-spherical porous fin. Additionally, temperature dependent internal heat generating condition, natural convection and radiation effects are also taken into account. The nonlinear form of an ordinary differential equation (ODE) along with boundary conditions is resolved using RKF 45 method. The numerical results are obtained for various physical constraints and the impact of these constraints on fin surface temperature is discussed via graphs. The results show that increasing an internal heat generation parameter raises temperature, whereas the opposite is true for radiation and convective parameters. Furthermore, the temperature of the hybrid nanofluid is consistently higher than the temperature of the nanofluid.